A monitoring device, system, and blur detection method of images separate a monitored area into an in-focus area and an out-of-focus area after focusing is done and then analyze the following captured images for how the blocks that makes up the in-focus area change in the blurriness and the proportion of the blocks with changed blurriness to overall blocks in the in-focus area. When the proportion of a captured image meets a specific condition, the captured image is then determined as a blur image. A consecutive number of determined blur images will trigger an auto focus procedure.
Legal claims defining the scope of protection, as filed with the USPTO.
1. A blur detection method of images, comprising steps: generating a reference image having a plurality of blocks; identifying a plurality of first blocks from the plurality of blocks, wherein an in-focus area is defined by the plurality of first blocks; generating a test image having a plurality of test blocks corresponding to the plurality of blocks of the reference image; identifying a plurality of second blocks from the plurality of test blocks that correspond to the plurality of first blocks in the in-focus area; and executing a determination procedure and generating a determination result based on information from the plurality of second blocks and the plurality of first blocks, and when the determination result meets a predetermined condition, determining the test image as a blurred image.
2. The blur detection method of claim 1 , wherein the steps of identifying the plurality of first blocks and the plurality of second blocks are identifying the plurality of first blocks and the plurality of second blocks according to a first threshold value.
3. The blur detection method of claim 2 , wherein identifying the plurality of first blocks according to the first threshold value is by comparing a contrast value of each block with the first threshold value to identify a plurality of blocks whose contrast values exceed the first threshold value as the plurality of first blocks.
4. The blur detection method of claim 3 , wherein identifying the plurality of second blocks according to the first threshold value is by comparing the contrast values of the plurality of first blocks of the reference image and the contrast values of the plurality of test blocks that correspond to the plurality of first blocks in the in-focus area to identify a plurality of test blocks that correspond to the plurality of first blocks in the in-focus area and have different contrast values as the plurality of second blocks.
5. The blur detection method of claim 4 , wherein when the number of the plurality of first blocks is M and the number of the plurality of second blocks is N, the determination procedure is dividing N by M and the determination result is a ratio of N divided by M, wherein M and N are positive integers and the predetermined condition is the ratio greater or equal to a second threshold value.
6. The blur detection method of claim 3 , wherein identifying the plurality of second blocks according to the first threshold value is by comparing the contrast values of the plurality of first blocks of the reference image and the contrast values of the plurality of test blocks that correspond to the plurality of first blocks in the in-focus area to identify a plurality of test blocks that correspond to the plurality of first blocks in the in-focus area and have substantially the same contrast values as the plurality of second blocks.
7. The blur detection method of claim 6 , wherein when the number of the plurality of first blocks is M and the number of the plurality of second blocks is N, the determination procedure is dividing N by M and the determination result is a ratio of N divided by M, wherein M and N are positive integers and the predetermined condition is the ratio smaller or equal to a third threshold value.
8. The blur detection method of claim 1 , further comprising steps: generating repeatedly a plurality of test images; determining whether each of the plurality of test images is a blurred image; and when consecutive P test images are determined as blurred images, starting an auto-focus procedure, wherein P is a positive integer larger than 1.
9. The blur detection method of claim 8 , further comprising step: generating a new reference image after the auto-focus procedure is finished.
10. The blur detection method of claim 1 , wherein the reference image and the test image are generated by using an image capturing unit capturing a scene, the blur detection method further comprising step: determining whether the scene being captured by the image capturing unit changes and generating a new reference image after the scene changes.
11. The blur detection method of claim 1 , wherein the reference image and the test image are generated by using an image capturing unit capturing a scene, the blur detection method further comprising step: determining whether a parameter of pan, a parameter of tilt, or a parameter of zoom of the image capturing unit changes and generating a new reference image after the parameter of pan, the parameter of tilt, or the parameter of zoom of the image capturing unit changes.
12. A monitoring device, comprising an image capturing unit and a processing unit, the image capturing unit and the processing unit performing the blur detection method of claim 1 .
13. A monitoring system, comprising a monitoring device having an image capturing unit and a first processing unit and comprising a remote processing device having a second processing unit, the monitoring device and the remote processing device performing the blur detection method of claim 1 .
Cooperative Patent Classification codes for this invention. Click any code to explore related patents in that topic.
August 18, 2015
September 27, 2016
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